shrutipandit707 / email-classifier-svm

EMail Spam Detection and Classification using SVM

Today emails have become to be a standout amongst the most well-known and efficient types of correspondence for Internet clients. Hence because of its fame, the email will be misused. One such misuse is the posting of unwelcome,undesirable messages known as spam or junk messages. Email spam has different consequences. It diminishes productivity,consumes additional space in mailboxes, additional time, expands programming damaging viruses, and materials that containconceivably destructive data for Internet clients, destroys the stability of mail servers, and subsequently, clients invest lots of time for sorting approaching mail and erasing undesirable correspondence. So there is a need for spam detection so that its outcomes can be reduced. In this notebook, I propose a novel method for email spam detection using SVM and feature extraction.

Table of Contents

• General Info
• Technologies Used
• Conclusions
• Acknowledgements

General Information

• Provide general information about your project here.

We will be using SVM Techniques for Email spam detection.

• What is the background of your project?

In this case study, we are attempting to solve a real world business problem using SVM techniques. We will be understanding and solving a Email Spam Detection and Classification.We will be checking how data can be used effectively to solve business problems like Email Spam Detection and Classification.

• Business Problem Statement:

Spam refers to unsolicited business email. Otherwise called junk mail, spam floods Internet client’s electronic mailboxes. These junk emails can contain different sorts of messages, for example, commercial advertising, pornography, business promoting, doubtful product, infections or quasi-legal services.

• What is the dataset that is being used?

The dataset can be downloaded here: https://archive.ics.uci.edu/ml/datasets/spambase

Conclusions

• The Spam is a standout amongst the most irritating and malicious increments to worldwide PC world. In this paper, we propose a novel method for email spam detection which can effectively identify the spam emails from its contents. The spam emails can be blocked by the user and genuine mail can be retained by the user.

Technologies Used

• Python - version 3.6.9
• Numpy - version 1.21.5
• Pandas - version 1.3.5
• Seaborn - version 0.11.2

Acknowledgements

Give credit here.

• This project was inspired by Upgrad.
• This project was based on Upgrad's Tutorial.

Contact

Created by [@shrutipandit707] - feel free to contact us!